# Computation and Data Science

> **NIH NIH P50** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2020 · $235,905

## Abstract

ABSTRACT
The Computation and Data Science Core provides a variety of computational capabilities that will support and
enhance discovery and illumination of HIV biology. We have created a flexible and robust protein engineering
platform that couples both design and screening approaches).1-10 These capabilities support de novo protein
design and optimization of ligand binding, assembly, stability, and solubility properties. Complementary
resources enable high-throughput screening using phage and yeast display.11 Computational modeling is
further bolstered by atomistic and coarse-grained molecular dynamics simulations that leverage experimental
datasets12,13 and multiscale parameterization strategies14-23 to model different interactions in the HIV life cycle
and generate testable hypotheses. Conceptual depth is added by a range of evolutionary genomics resources,
including phylogenetic and discovery pipelines that draw on primate diversity to inform human biology and
provide access to primate gene sequences and cDNA clones to extend our biochemical and structural
studies.24-27 Finally, we have established unique capabilities in molecular animation, scientific communication,
and public outreach that feature the creation and dissemination of sophisticated, dynamic 3D visualizations of
biological processes.

## Key facts

- **NIH application ID:** 9993252
- **Project number:** 5P50AI150464-14
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Nels C. Elde
- **Activity code:** P50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $235,905
- **Award type:** 5
- **Project period:** 2007-08-27 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9993252

## Citation

> US National Institutes of Health, RePORTER application 9993252, Computation and Data Science (5P50AI150464-14). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/9993252. Licensed CC0.

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